Geographic variation in 5-year mortality following HIV diagnosis: implications for clinical interventions

Characterizing spatial distribution of HIV outcomes is vital for targeting interventions to areas most at risk. We performed spatial analysis to identify geographic clusters and factors associated with mortality in KwaZulu-Natal, South Africa. We utilized Sizanani trial (NCT01188941) data, which enrolled participants August 2010-January 2013 and obtained vital status at 5.8 (IQR 5.0-6.4) years of follow-up. We mapped geocoded addresses to 2011 Census-defined small area layer (SAL) centroids, used Kulldorff's spatial scan statistic to identify mortality clusters, and compared socio-demographic factors for SALs within and outside mortality clusters. We assigned 1,143 participants living with HIV (260 [23%] of whom died during follow-up) to 677 SALs. One lower mortality cluster (n = 90, RR = 0.23, p = 0.022) was identified near a hospital outside Durban. SALs in the cluster were younger (24y vs 25y, p < 0.001); had fewer bedrooms/household (3 vs 4, p < 0.001); had more females (52% vs 51%, p = 0.013) and residents with no schooling past age 20 (4% vs 3%, p < 0.001) or no education at all (4% vs 3%, p < 0.001); had fewer residents with income >3,200 ZAR/month (5% vs 9%, p < 0.001); and had reduced access to piped water (p < 0.001), refuse disposal (p < 0.001), and toilets (p < 0.001). Targeted interventions may improve outcomes in areas with similar characteristics.

Remote Sensing Provides a Rapid Epidemiological Context for the Control of African Swine Fever in Germany

Transboundary disease control, as for African swine fever (ASF), requires rapid understanding of the locally relevant potential risk factors. Here, we show how satellite remote sensing can be applied to the field of animal disease control by providing an epidemiological context for the implementation of measures against the occurrence of ASF in Germany. We find that remotely sensed observations are of the greatest value at a lower jurisdictional level, particularly in support of wild boar carcass search efforts.

Spatio-Temporal Water Hyacinth Monitoring in the Lower Mondego (Portugal) Using Remote Sensing Data

Monitoring invasive plant species is a crucial task to assess their presence in affected ecosystems. However, it is a laborious and complex task as it requires vast surface areas, with difficult access, to be surveyed. Remotely sensed data can be a great contribution to such operations, especially for clearly visible and predominant species. In the scope of this study, water hyacinth (Eichhornia crassipes) was monitored in the Lower Mondego region (Portugal). For this purpose, Sentinel-2 satellite data were explored enabling us to follow spatial patterns in three water channels from 2018 to 2021. By applying a straightforward and effective methodology, it was possible to estimate areas that could contain water hyacinth and to obtain the total surface area occupied by this invasive species. The normalized difference vegetation index (NDVI) was used for this purpose. It was verified that the occupation of this invasive species over the study area exponentially increases from May to October. However, this increase was not verified in 2021, which could be a consequence of the adopted mitigation measures. To provide the results of this study, the methodology was applied through a semi-automatic geographic information system (GIS) application. This tool enables researchers and ecologists to apply the same approach in monitoring water hyacinth or any other invasive plant species in similar or different contexts. This methodology proved to be more effective than machine learning approaches when applied to multispectral data acquired with an unmanned aerial vehicle. In fact, a global accuracy greater than 97% was achieved using the NDVI-based approach, versus 93% when using the machine learning approach (above 93%).

Antifragile and Resilient Geographical Information System Service Delivery in Fog Computing

The demand for cloud computing has drastically increased recently, but this paradigm has several issues due to its inherent complications, such as non-reliability, latency, lesser mobility support, and location-aware services. Fog computing can resolve these issues to some extent, yet it is still in its infancy. Despite several existing works, these works lack fault-tolerant fog computing, which necessitates further research. Fault tolerance enables the performing and provisioning of services despite failures and maintains anti-fragility and resiliency. Fog computing is highly diverse in terms of failures as compared to cloud computing and requires wide research and investigation. From this perspective, this study primarily focuses on the provision of uninterrupted services through fog computing. A framework has been designed to provide uninterrupted services while maintaining resiliency. The geographical information system (GIS) services have been deployed as a test bed which requires high computation, requires intensive resources in terms of CPU and memory, and requires low latency. Keeping different types of failures at different levels and their impacts on service failure and greater response time in mind, the framework was made anti-fragile and resilient at different levels. Experimental results indicate that during service interruption, the user state remains unaffected.

Mortality due to noninfectious lower respiratory diseases: A spatiotemporal, cross-sectional study

Background and Aims

Geography plays an important role in the incidence of respiratory diseases. The aim of this study was to investigate the epidemiology and geographical distribution of death due to noninfectious lower respiratory diseases (NILRDs).

Methods

Data related to all death due to NILRD in Kerman Province between 2012 and 2018 were extracted from the National Mortality Registry. The underlying causes of death were extracted from the registry based on the assigned codes from ICD-10 (International Classification of Diseases 10th Revision) classification. The existence of spatial clusters and outliers was evaluated using local indicators of spatial association statistics.

Results

The frequency of death due to NILRD was 8005 persons during the 7 years of the study. The main cause of death was chronic lower respiratory disease (54.2%). Other causes of death were, respectively, lung diseases due to external agents (1.09%), other respiratory diseases mainly affecting the interstitium (1.16%), other diseases of pleura (0.57%), and other diseases of the respiratory system (42.13%). The age- and sex-adjusted mortality rates due to NILRD in the north and center of the province increased significantly from 2012 to 2018. Also, the results of cluster analysis identified northern regions as the clustered areas of NILRD.

Conclusions

Our findings showed a significant increase in mortality due to NILRD in Kerman Province during the 7 years of the study. To reduce this type of death, health policymakers should have environmental health plans and basic solutions, such as a warning system to reduce the commuting on highly air-polluted days and to control pollutants, especially in the industrial areas of the north of this province.

Sociodemographic Variations in the Availability of Urban Green Spaces in an Older Swedish Population

Urban green spaces (UGS) can have a positive impact on health and thereby potentially ease the strain on the health care system. However, the availability and benefits seem to vary between different sociodemographic groups. The aim of this study was to investigate associations between sociodemographic factors and availability to UGS among people aged 65 years or older. Data on sociodemographic variables and residential coordinates were obtained for three cross-sectional cohorts in two cities (Malmö and Kristianstad) and three years (2010, 2015, and 2019). Three measures of urban green spaces; total (UGS), public (PGS) and quiet (QGS), within 300 m were used to determine availability. The results indicated higher availability to both total and publicly available urban green spaces for groups with lower socioeconomic status (SES) is positive from a health perspective. However, availability to high qualitative publicly available urban green spaces, from a noise perspective, was lower, indicating the opposite.

Geographic barriers to achieving universal health coverage: evidence from rural Madagascar

Poor geographic access can persist even when affordable and well-functioning health systems are in place, limiting efforts for universal health coverage (UHC). It is unclear how to balance support for health facilities and community health workers in UHC national strategies. The goal of this study was to evaluate how a health system strengthening (HSS) intervention aimed towards UHC affected the geographic access to primary care in a rural district of Madagascar. For this, we collected the fokontany of residence (lowest administrative unit) from nearly 300 000 outpatient consultations occurring in facilities of Ifanadiana district in 2014-2017 and in the subset of community sites supported by the HSS intervention. Distance from patients to facilities was accurately estimated following a full mapping of the district's footpaths and residential areas. We modelled per capita utilization for each fokontany through interrupted time-series analyses with control groups, accounting for non-linear relationships with distance and travel time among other factors, and we predicted facility utilization across the district under a scenario with and without HSS. Finally, we compared geographic trends in primary care when combining utilization at health facilities and community sites. We find that facility-based interventions similar to those in UHC strategies achieved high utilization rates of 1-3 consultations per person year only among populations living in close proximity to facilities. We predict that scaling only facility-based HSS programmes would result in large gaps in access, with over 75% of the population unable to reach one consultation per person year. Community health delivery, available only for children under 5 years, provided major improvements in service utilization regardless of their distance from facilities, contributing to 90% of primary care consultations in remote populations. Our results reveal the geographic limits of current UHC strategies and highlight the need to invest on professionalized community health programmes with larger scopes of service.

National analysis of the Modified Monash Model, population distribution and a socio-economic index to inform rural health workforce planning

AIMS

To describe the population distribution and socio-economic position of residents across all states and territories of Australia, stratified using the 7 Modified Monash Model classifications. The numerical summary, and the methods described, can be applied by a variety of end users including workforce planners, researchers, policy-makers and funding bodies for guiding future investment under different scenarios, and aid in evaluating geographically focused programs.

CONTEXT

The Commonwealth Department of Health is transitioning to the Modified Monash Model to objectively describe geographical access. This change applies to the Rural Health Multidisciplinary Training Program, one of the Australian Government's key policies to address the maldistribution of the rural health workforce. Unlike the previously applied Australian Statistical Geography Standard-Remoteness Areas, a summary of the population in each Modified Monash Model classification is not available, nor is a socio-economic overview of the communities within these areas.

APPROACH

Spatial analysis of Australian Bureau of Statistics data (Modified Monash Model, population data and the Index of Relative Socio-economic Advantage and Disadvantage collected or derived from the 2016 census) at the Statistical Area 1-the smallest unit for the release of census data.

CONCLUSION

Linking the Modified Monash Model, a socio-economic index and granular population data at the national level highlights the disadvantage of many residents in small rural towns (Modified Monash 5). The Modified Monash Model does not exhibit a continuum of the largest population residing in the most accessible classification and the smallest population residing in the least accessible classification that is seen in the Australian Statistical Geography Standard-Remoteness Areas. Coupled with policy relevance, the advantage of using the Modified Monash Model as the basis for analysis is that it highlights areas that have both a critical mass of residents and differing levels of socio-economic advantage and disadvantage. This will help end users to target funding to those regions where there is potential to improve access to services for the greatest number of rural residents.

Epidemiology and Spatial Emergence of Anaplasmosis, New York, USA, 2010‒2018

Human granulocytic anaplasmosis, a tickborne disease caused by the bacterium Anaplasma phagocytophilum, was first identified during 1994 and is now an emerging public health threat in the United States. New York state (NYS) has experienced a recent increase in the incidence of anaplasmosis. We analyzed human case surveillance and tick surveillance data collected by the NYS Department of Health for spatiotemporal patterns of disease emergence. We describe the epidemiology and growing incidence of anaplasmosis cases reported during 2010–2018. Spatial analysis showed an expanding hot spot of anaplasmosis in the Capital Region, where incidence increased >8-fold. The prevalence of A. phagocytophilum increased greatly within tick populations in the Capital Region over the same period, and entomologic risk factors were correlated with disease incidence at a local level. These results indicate that anaplasmosis is rapidly emerging in a geographically focused area of NYS, likely driven by localized changes in exposure risk.

Walkability and Greenness Do Not Walk Together: Investigating Associations between Greenness and Walkability in a Large Metropolitan City Context

BACKGROUND

The existing environment literature separately emphasizes the importance of neighborhood walkability and greenness in enhancing health and wellbeing. Thus, a desirable neighborhood should ideally be green and walkable at the same time. Yet, limited research exists on the prevalence of such "sweet spot" neighborhoods. We sought to investigate this question in the context of a large metropolitan city (i.e., Sydney) in Australia.

METHODS

Using suburb level normalized difference vegetative index (NDVI), percentage urban greenspace, Walk Score^® (Walk Score, Seattle, WA, USA), and other data, we explored the global and local relationships of neighborhood-level greenness, urban green space (percent park area) with walkability applying both non-spatial and spatial modeling.

RESULTS

We found an overall negative relationship between walkability and greenness (measured as NDVI). Most neighborhoods (represented by suburbs) in Sydney are either walkable or green, but not both. Sweet spot neighborhoods that did exist were green but only somewhat walkable. In addition, many neighborhoods were both less green and somewhat walkable. Moreover, we observed a significant positive relationship between percentage park area and walkability. These results indicate walkability and greenness have inverse and, at best, mixed associations in the Sydney metropolitan area.

CONCLUSIONS

Our analysis indicates an overall negative relationship between greenness and walkability, with significant local variability. With ongoing efforts towards greening Sydney and improving walkability, more neighborhoods may eventually be transformed into becoming greener and more walkable.

From Testing to Decision-Making: A Data-Driven Analytics COVID-19 Response

In March 2020, NorthShore University Health System laboratories mobilized to develop and validate polymerase chain reaction based testing for detection of SARS-CoV-2. Using laboratory data, NorthShore University Health System created the Data Coronavirus Analytics Research Team to track activities affected by SARS-CoV-2 across the organization. Operational leaders used data insights and predictions from Data Coronavirus Analytics Research Team to redeploy critical care resources across the hospital system, and real-time data were used daily to make adjustments to staffing and supply decisions. Geographical data were used to triage patients to other hospitals in our system when COVID-19 detected pavilions were at capacity. Additionally, one of the consequences of COVID-19 was the inability for patients to receive elective care leading to extended periods of pain and uncertainty about a disease or treatment. After shutting down elective surgeries beginning in March of 2020, NorthShore University Health System set a recovery goal to achieve 80% of our historical volumes by October 1, 2020. Using the Data Coronavirus Analytics Research Team, our operational and clinical teams were able to achieve 89% of our historical volumes a month ahead of schedule, allowing rapid recovery of surgical volume and financial stability. The Data Coronavirus Analytics Research Team also was used to demonstrate that the accelerated recovery period had no negative impact with regard to iatrogenic COVID-19 infection and did not result in increased deep vein thrombosis, pulmonary embolisms, or cerebrovascular accident. These achievements demonstrate how a coordinated and transparent data-driven effort that was built upon a robust laboratory testing capability was essential to the operational response and recovery from the COVID-19 crisis.

GIS-Facilitated Effective Propagation Protocols of the Endangered Local Endemic of Crete Carlina diae (Rech. f.) Meusel and A. Kástner (Asteraceae): Serving Ex Situ Conservation Needs and Its Future Sustainable Utilization as an Ornamental

Conservation and sustainable exploitation of threatened endemic plants with medicinal and/or horticultural/ornamental value can be achieved through the development of effective propagation protocols. After unveiling the bioclimatic preferences of Carlina diae (Asteraceae) with geographic information systems (GIS), four propagation trials were conducted using seeds of this endangered local Cretan endemic for in vivo and in vitro germination, as well as seasonal vegetative propagation trials (softwood cuttings) and micropropagation (nodal explants). Seed germination was accomplished at a level of 77–90% in vivo (30 days) and 96% in vitro (10 days) using an MS medium with 2.9 μM gibberellic acid (GA₃). The optimum treatments for cuttings’ rooting were 1000 and 2000 ppm indole-3-butyric acid (IBA) (11–16 roots, 2–3 cm long, 100% rooting) within 40 days in mist. In vitro shoot propagation exhibited a 2.8 proliferation rate after six successive subcultures on an MS medium with 2.9 μM GA₃. Both ex vitro rooting and acclimatization were successful in 40 days, with 96% microshoot rooting and an equal survival rate. The GIS-facilitated effective species-specific propagation protocols developed in this study can consolidate the perspective of successful re-introduction of ex situ-raised material of C. diae into wild habitats and may serve its sustainable exploitation for high-added value ornamental products.

Review of road accident analysis using GIS technique

The number of road crashes is significantly growing worldwide. In the transportation sector, accident outcomes are usually the loss of lives and injuries. To avoid further damages, a tool entitled geographical information system (GIS) could be helpful. GIS has the most demanding tools used to analyze road accidents and road design that can be noteworthy in traffic accident prevention. The purpose of this review is to propose the superlative approach of GIS applicable to accident analysis in different circumstances. The reviewed statistical results of accidents are performed by GIS but the numerical study is not consummate by GIS. Mainly, four essential GIS techniques are introduced and discussed in this review paper to simulate road accidents and suggest some prolific accident analysis tools for road safety.

The association between sporadic Legionnaires' disease and weather and environmental factors, Minnesota, 2011-2018

From 2011 through 2018, there was a notable increase in sporadic Legionnaires' disease in the state of Minnesota. Sporadic cases are those not associated with a documented outbreak. Outbreak-related cases are typically associated with a common identified contaminated water system; sporadic cases typically do not have a common source that has been identified. Because of this, it is hypothesised that weather and environmental factors can be used as predictors of sporadic Legionnaires' disease. An ecological design was used with case report surveillance data from the state of Minnesota during 2011 through 2018. Over this 8-year period, there were 374 confirmed Legionnaires' disease cases included in the analysis. Precipitation, temperature and relative humidity (RH) data were collected from weather stations across the state. A Poisson regression analysis examined the risk of Legionnaires' disease associated with precipitation, temperature, RH, land-use and age. A lagged average 14-day precipitation had the strongest association with Legionnaires' disease (RR 2.5, CI 2.1-2.9), when accounting for temperature, RH, land-use and age. Temperature, RH and land-use also had statistically significant associations to Legionnaires' disease, but with smaller risk ratios. This study adds to the body of evidence that weather and environmental factors play an important role in the risk of sporadic Legionnaires' disease. This is an area that can be used to target additional research and prevention strategies.

Using open-source data to explore distribution of built environment characteristics across Kerala, India

Background

Built environment characteristics in the neighborhood are of utmost priority for a healthy lifestyle in the fast-urbanizing countries. These characteristics are closely linked to the disease burden and challenges in low- and middle-income countries (LMICs), which have been unexplored using open-source data. The present technology offers online resources and open source software that enable researchers to explore built environment characteristics with health and allied phenomena.

Objectives

This article intends to delineate methods to capture available and accessible objective built environment variables for a state in India and determine their distribution across the state.

Methods

Built environment variables such as population density and residential density were collated from the Census of India. Safety from crime and traffic were captured as crime rates and pedestrian accident rates, respectively, acquired from State Crime Records Bureau. Greenness, built-up density, and land slope were gathered from open-source satellite imagery repository. Road intersection density was derived from OpenStreetMap. Processing and analysis differed for each dataset depending on its source and nature.

Results

Each variable showed a distinct pattern across the state. Population and residential density were found to be closely related to each other across both districts and subdistricts. They were both positively related to crime rates, pedestrian accident rates, built-up density, and intersection density, whereas negatively related to land slope and greenness across the subdistricts.

Conclusion

Delineating the distribution of built environment variables using available and open-source data in resource-poor settings is a first in public health research among LMICs. Cost-effectiveness and reproducible nature of open-source solutions could equip researchers in resource-poor settings to identify built environment characteristics and patterns across regions.

Extension of the known distribution of a novel clade C betacoronavirus in a wildlife host

Disease surveillance in wildlife populations presents a logistical challenge, yet is critical in gaining a deeper understanding of the presence and impact of wildlife pathogens. Erinaceus coronavirus (EriCoV), a clade C Betacoronavirus, was first described in Western European hedgehogs (Erinaceus europaeus) in Germany. Here, our objective was to determine whether EriCoV is present, and if it is associated with disease, in Great Britain (GB). An EriCoV-specific BRYT-Green® real-time reverse transcription PCR assay was used to test 351 samples of faeces or distal large intestinal tract contents collected from casualty or dead hedgehogs from a wide area across GB. Viral RNA was detected in 10.8% (38) samples; however, the virus was not detected in any of the 61 samples tested from Scotland. The full genome sequence of the British EriCoV strain was determined using next generation sequencing; it shared 94% identity with a German EriCoV sequence. Multivariate statistical models using hedgehog case history data, faecal specimen descriptions and post-mortem examination findings found no significant associations indicative of disease associated with EriCoV in hedgehogs. These findings indicate that the Western European hedgehog is a reservoir host of EriCoV in the absence of apparent disease.

MoreAir: A Low-Cost Urban Air Pollution Monitoring System

MoreAir is a low-cost and agile urban air pollution monitoring system. This paper describes the methodology used in the development of this system along with some preliminary data analysis results. A key feature of MoreAir is its innovative sensor deployment strategy which is based on mobile and nomadic sensors as well as on medical data collected at a children’s hospital, used to identify urban areas of high prevalence of respiratory diseases. Another key feature is the use of machine learning to perform prediction. In this paper, Moroccan cities are taken as case studies. Using the agile deployment strategy of MoreAir, it is shown that in many Moroccan neighborhoods, road traffic has a smaller impact on the concentrations of particulate matters (PM) than other sources, such as public baths, public ovens, open-air street food vendors and thrift shops. A geographical information system has been developed to provide real-time information to the citizens about the air quality in different neighborhoods and thus raise awareness about urban pollution.

A cluster of Legionnaires' disease in Belgium linked to a cooling tower, August-September 2016: practical approach and challenges

A cluster of Legionnaires' disease (LD) with 10 confirmed, three probable and four possible cases occurred in August and September 2016 in Dendermonde, Belgium. The incidence in the district was 7 cases/100 000 population, exceeding the maximum annual incidence in the previous 5 years of 1.5/100 000. Epidemiological, environmental and geographical investigations identified a cooling tower (CT) as the most likely source. The case risk around the tower decreased with increasing distance and was highest within 5 km. Legionella pneumophila serogroup 1, ST48, was identified in a human respiratory sample but could not be matched with the environmental results. Public health authorities imposed measures to control the contamination of the CT and organised follow-up sampling. We identified obstacles encountered during the cluster investigation and formulated recommendations for improved LD cluster management, including faster coordination of teams through the outbreak control team, improved communication about clinical and environmental sample analysis, more detailed documentation of potential exposures obtained through the case questionnaire and earlier use of a geographical information tool to compare potential sources and for hypothesis generation.

Recruitment strategies and challenges: Lessons learned from a coal ash and children's health study

The purpose of this paper is to describe the approaches and recruitment strategies of a study focused on the impact of coal fly ash on neurobehavioral performance among children living in proximity to coal-burning power plants. Challenges encountered with each recruitment approach are highlighted as well as solutions used to overcome those challenges and ultimately enroll children and one of their parents or guardians. To ensure participants were distributed throughout the study area, geographical information systems were used to guide recruitment and achieve the target sample size (N = 300). Several approaches were employed to recruit the number of needed participants, including "shoe leather" or door-to-door recruitment, placement of flyers and brochures in public spaces, mailings to targeted addresses, media announcements, and local government outreach. Since September 2015, 265 participants have been enrolled in the study using a combination of the described recruitment approaches. Even with a well-designed plan, it is important to re-examine strategies at every step to maximize recruitment efforts. Researcher flexibility in adapting to new strategies is vital in facilitating recruitment efforts, and the recruitment of participants in the study remains a dynamic and evolving process.

Technology Support for Collaborative Preparation of Emergency Plans

Preparing a plan for reaction to a grave emergency is a significant first stage in disaster management. A group of experts can do such preparation. Best results are obtained with group members having diverse backgrounds and access to different relevant data. The output of this stage should be a plan as comprehensive as possible, taking into account various perspectives. The group can organize itself as a collaborative decision-making team with a process cycle involving modeling the process, defining the objectives of the decision outcome, gathering data, generating options and evaluating them according to the defined objectives. The meeting participants may have their own evidences concerning people's location at the beginning of the emergency and assumptions about people's reactions once it occurs. Geographical information is typically crucial for the plan, because the plan must be based on the location of the safe areas, the distances to move people, the connecting roads or other evacuation links, the ease of movement of the rescue personnel, and other geography-based considerations. The paper deals with this scenario and it introduces a computer tool intended to support the experts to prepare the plan by incorporating the various viewpoints and data. The group participants should be able to generate, visualize and compare the outcomes of their contributions. The proposal is complemented with an example of use: it is a real case simulation in the event of a tsunami following an earthquake at a certain urban location.

Effect of changes in green spaces on mental health in older adults: a fixed effects analysis

Background

Urban green spaces have been linked to different health benefits, but longitudinal studies on the effect of green spaces on mental health are sparse and evidence often inconclusive. Our objective was to study the effect of changes in green spaces in the residential environment on changes in mental health using data with 10 years of follow-up (2004–2014).

Methods

Data from 3175 Dutch adults were linked to accessibility and availability measures of green spaces at three time points (2004/2011/2014). Mental health was measured with the Mental Health Inventory-5. Fixed effects analyses were performed to assess the effect of changes in green spaces on mental health.

Results

Cross-sectional analysis of baseline data showed significant associations between Euclidean distances to the nearest green space and mental health, with an increase of 100 m correlating with a lower mental health score of approximately 0.5 (95% CI −0.87 to −0.12) on a 0–100 scale. Fixed effects models showed no evidence for associations between changes in green spaces and changes in mental health both for the entire sample as well as for those that did not relocate during follow-up.

Conclusions

Despite observed cross-sectional correlations between the accessibility of green space in the residential environment and mental health, no evidence was found for an association between changes in green spaces and changes in mental health. If mental health and green spaces are indeed causally linked, then changes in green spaces in the Eindhoven area between 2004 and 2014 are not enough to produce a significant effect.

Model of Risk of Exposure to Lyme Borreliosis and Tick-Borne Encephalitis Virus-Infected Ticks in the Border Area of the Czech Republic (South Bohemia) and Germany (Lower Bavaria and Upper Palatinate)

In Europe, Lyme borreliosis (LB) and tick-borne encephalitis (TBE) are the two vector-borne diseases with the largest impact on human health. Based on data on the density of host-seeking Ixodes ricinus ticks and pathogen prevalence and using a variety of environmental data, we have created an acarological risk model for a region where both diseases are endemic (Czech Republic-South Bohemia and Germany-Lower Bavaria, Upper Palatinate). The data on tick density were acquired by flagging 50 sampling sites three times in a single season. Prevalence of the causative agents of LB and TBE was determined. Data on environmental variables (e.g., altitude, vegetation cover, NDVI, land surface temperature) were obtained from various sources and processed using geographical information systems. Generalized linear models were used to estimate tick density, probability of tick infection, and density of infected ticks for the whole area. A significantly higher incidence of human TBE cases was recorded in South Bohemia compared to Bavarian regions, which correlated with a lower tick density in Bavaria. However, the differences in pathogen prevalence rates were not significant. The model outputs were made available to the public in the form of risk maps, indicating the distribution of tick-borne disease risk in space.

Inter-Regional Differences in Travel Time to the Nearest Nursery for Children with Mild Acute Illness in Japan

Access to day-care services for children with mild acute illness is important for working parents, because infants and toddlers often suddenly become ill, and most Japanese nursery schools do not accept children with even mild illnesses. Actual travel time to nurseries providing such day-care services is one of the indicators for measuring accessibility. However, this variable has not been well analyzed in previous work. To clarify practical access to such nurseries, this study used a car navigation algorithm to calculate the percentage of the population of children in Japan who can access nurseries providing services for children with mild acute illnesses within 15 to 30 minutes and compared this with the proportion of children living within a linear distance of 10 km of such nurseries. Of the 4,987,706 children younger than 5 years in 2015, 51.7% lived in areas from which the nearest nursery for children with mild acute illness was accessible within 0-15 minutes by automobile. In addition, 81.5% lived within 0-30 minutes of such nurseries, and the same percentage (81.5%) lived within a linear distance of 10 km of such nurseries. Both calculation methods (travel time and linear distance) showed inter-regional differences in accessibility, and the proportion of children with access to these nurseries was higher in heavily populated regions (e.g., Kanto and Kinki) than in less populated regions (e.g., Hokkaido and Tohoku). Children and caregivers throughout Japan should have equal access to these nurseries, because the national government subsidizes such services.

Beyond bus fare: deconstructing prenatal care travel among low-income urban mothers through a mix methods GIS study

OBJECTIVE

Guided by critical theory, this study illustrates the value of interpretative mapping to deconstruct bus travel to publicly funded prenatal care in a city marked by health and social inequities.

METHODS

This mixed methods study used GIS maps based on 61,305 births to study the known barrier of transportation to prenatal care among urban mothers most at risk for preterm birth.

RESULTS

Among 350 census tracts, 36 census tracts had preterm rates between 25 -36.9%. Modeling travel time for the case vignette for routine prenatal care took 21 visits to different geographically located facilities. This burden increased to 32 visits if the case vignette was high-risk.

CONCLUSIONS

Interpretative GIS mapping is an important tool to ground truth spatially linked data into real world meanings. Promoting optimal health requires innovative and feasible approaches that take into consideration daily maternal functioning as pregnant mothers care for their children and themselves.

Climatic adaptation and ecological descriptors of wild beans from Mexico

Despite its economic, social, biological, and cultural importance, wild forms of the genus Phaseolus are not well represented in germplasm banks, and they are at great risk due to changes in land use as well as climate change. To improve our understanding of the potential geographical distribution of wild beans (Phaseolus spp.) from Mexico and support in situ and ex situ conservation programs, we determined the climatic adaptation ranges of 29 species and two subspecies of Phaseolus collected throughout Mexico. Based on five biotic and 117 abiotic variables obtained from different databases-WorldClim, Global-Aridity, and Global-PET-we performed principal component and cluster analyses. Germplasm was distributed among 12 climatic types from a possible 28. The general climatic ranges were as follows: 8-3,083 m above sea level; 12.07-26.96°C annual mean temperature; 10.33-202.68 mm annual precipitation; 9.33-16.56 W/m2 of net radiation; 11.68-14.23 hr photoperiod; 0.06-1.57 aridity index; and 10-1,728 mm/month of annual potential evapotranspiration. Most descriptive variables (25) clustered species into two groups: One included germplasm from semihot climates, and the other included germplasm from temperate climates. Species clustering showed 45% to 54% coincidence with species previously grouped using molecular data. The species P. filiformis, P. purpusii, and P. maculatus were found at low-humidity locations; these species could be used to improve our understanding of the extreme aridity adaptation mechanisms used by wild beans to avoid or tolerate climate change as well as to introgress favorable alleles into new cultivars adapted to hot, dry environments.

Relationship between Travel Time from Home to a Regional Sleep Apnea Clinic in British Columbia, Canada, and the Severity of Obstructive Sleep

RATIONALE

In the majority of people with obstructive sleep apnea, the disorder remains undiagnosed. This may be partly a result of inadequate access to diagnostic sleep services. We thus hypothesized that even modest travel times to a sleep clinic may delay diagnosis and reduce detection of milder disease.

OBJECTIVES

We sought to determine whether travel time between an individual's home and a sleep clinic is associated with sleep apnea severity at presentation.

METHODS

We recruited patients referred for suspected sleep apnea to the University of British Columbia Hospital Sleep Clinic between May 2003 and July 2011. The patient's place of residence was geocoded at the postal code level. Travel times between the population-weighted dissemination areas for each patient and the sleep clinic were calculated using ArcGIS (ESRI, Redlands, CA) network analyst and the Origin-Destination matrix function. All patients underwent full polysomnography.

MEASUREMENTS AND MAIN RESULTS

There were 1,275 patients; 69% were male, the mean age was 58 years. (SD = 11.9), and the mean apnea-hypopnea index was 22 per hour (SD = 21.6). In the univariate model, travel time was a significant predictor of obstructive sleep apnea severity (P = 0.02). After controlling for confounders including sex, age, obesity, and education, travel time remained a significant predictor of sleep apnea severity (P < 0.01). In the multivariate model, each increase in 10 minutes of travel time was associated with an increase in the apnea-hypopnea index of 1.4 events per hour.

CONCLUSIONS

For reasons that remain to be determined, travel times are associated with the severity of obstructive sleep apnea at presentation to a sleep clinic. If the results can be verified at other centers, this may help guide the geographic distribution of sleep centers within a health care system.

Social Disequilibrium and the Risk of HIV Acquisition: A Multilevel Study in Rural KwaZulu-Natal Province, South Africa

BACKGROUND

Few population-based multilevel studies have quantified the risks that social context poses in rural communities with high HIV incidence across South Africa. We investigated the individual, social, and community challenges to HIV acquisition risk in areas with high and low incidence of HIV infection (hotspots/coldspots).

METHODS

The cohort (N = 17,376) included all HIV-negative adults enrolled in a population-based HIV surveillance study from 2004 to 2015 in a rural South African community with large labor migrancy. Multilevel survival models were fitted to examine the social determinants (ie, neighborhood migration intensity), community traits (ie, HIV prevalence), and individual determinants of HIV acquisition risk in identified hotspots/coldspots.

RESULTS

The HIV acquisition risk (adjusted hazard ratio [aHR] = 1.05, 95% confidence interval [CI]: 1.01 to 1.09) was greater in hotspots with higher neighborhood migration intensity among men. In women, higher neighborhood migration intensity (aHR = 1.02, 95% CI: 1.01 to 1.02) was associated with a greater HIV acquisition risk, irrespective of whether they lived in hotspot/coldspot communities. HIV acquisition risk was greater in communities with a higher prevalence of HIV in both men (aHR = 1.07, 95% CI: 1.03 to 1.12) and women (aHR = 1.03, 95% CI: 1.01 to 1.05), irrespective of hotspot/coldspot locations.

CONCLUSION

HIV acquisition risk was strongly influenced by gender (ie, young women), behavior (ie, sexual debut, contraception, circumcision), and social determinants. Certain challenges (ie, community disease prevalence) for HIV acquisition risk impacted both sexes, regardless of residence in hotspot/coldspot communities, whereas social determinants (ie, neighborhood migration intensity) were pronounced in hotspots among men. Future intervention scale-up requires addressing the social context that contributes to HIV acquisition risk in rural areas with high migration.

A Mesoamerican origin of cherimoya (Annona cherimola Mill.): Implications for the conservation of plant genetic resources

Knowledge on the structure and distribution of genetic diversity is a key aspect to plan and execute an efficient conservation and utilization of the genetic resources of any crop as well as for determining historical demographic inferences. In this work, a large data set of 1,765 accessions of cherimoya (Annona cherimola Mill, Annonaceae), an underutilized fruit tree crop native to the Neotropics and used as a food source by pre-Columbian cultures, was collected from six different countries across the American continent and amplified with nine highly informative microsatellite markers. The structure analyses, fine representation of the genetic diversity and an ABC approach suggest a Mesoamerican origin of the crop, contrary to previous reports, with clear implications for the dispersion of plant germplasm between Central and South America in pre-Columbian times. These results together with the potential distribution of the species in a climatic change context using two different climate models provide new insights for the history and conservation of extant genetic resources of cherimoya that can be applied to other currently underutilized woody perennial crops.

Collaborating to Create Healthier Communities

The Montgomery County United Way and Sam Houston State University explored existing public health and community-based issues and associated assets and gaps within Montgomery County, Texas, through the integration of quantitative geospatial data, demographic information, and the application of geographical information systems. The intent of the initial results was to use maps to visually compare the magnitude of significant emerging health issues in Montgomery County with other counties across Texas in an effort to better educate and increase the awareness of the general public within Montgomery County. The second objective was to present an example of the visual effect and impact of the overall spatial analysis and mapping process with a focus on a specific community issue that could likely be addressed and potentially solved in a relatively short amount of time. This second and more spatially detailed aspect of the evaluation resulted in the creation of an asset map that presented high concentrations or densities of payday loan services in Montgomery County. Recognizing the potential risks of payday loans, Montgomery County United Way presented the asset maps to the effected community leaders. Upon review, leaders discovered there were dense clusters of payday loan sites in areas with high rates of poverty. Prior to the creation of this aggregated payday loan business location map, an individual in a community typically only saw one, or two at the most, payday loan business during a daily commute. Within a very short period and through a grassroots effort to improve community well-being, there were significant formal and positive changes made by the community.

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara

Recent progress in large-scale georeferenced data collection is widening opportunities for combining multi-disciplinary datasets from biophysical to socioeconomic domains, advancing our analytical and modeling capacity. Granular spatial datasets provide critical information necessary for decision makers to identify target areas, assess baseline conditions, prioritize investment options, set goals and targets and monitor impacts. However, key challenges in reconciling data across themes, scales and borders restrict our capacity to produce global and regional maps and time series. This paper provides overview, structure and coverage of CELL5M—an open-access database of geospatial indicators at 5 arc-minute grid resolution—and introduces a range of analytical applications and case-uses. CELL5M covers a wide set of agriculture-relevant domains for all countries in Africa South of the Sahara and supports our understanding of multi-dimensional spatial variability inherent in farming landscapes throughout the region.

A geostatistical investigation of agricultural and infrastructural risk factors associated with primary verotoxigenic E. coli (VTEC) infection in the Republic of Ireland, 2008-2013

Ireland reports the highest incidence of verotoxigenic Escherichia coli (VTEC) infection in Europe. This study investigated potential risk factors for confirmed sporadic and outbreak primary VTEC infections during 2008-2013. Overall, 989 VTEC infections including 521 serogroup O157 and 233 serogroup O26 were geo-referenced to 931 of 18 488 census enumeration areas. The geographical distribution of human population, livestock, unregulated groundwater sources, domestic wastewater treatment systems (DWWTS) and a deprivation index were examined relative to notification of VTEC events in 524 of 6242 rural areas. Multivariate modelling identified three spatially derived variables associated with VTEC notification: private well usage [odds ratio (OR) 6·896, P < 0·001], cattle density (OR 1·002, P < 0·001) and DWWTS density (OR 0·978, P = 0·002). Private well usage (OR 18·727, P < 0·001) and cattle density (OR 1·001, P = 0·007) were both associated with VTEC O157 infection, while DWWTS density (OR 0·987, P = 0·028) was significant within the VTEC O26 model. Findings indicate that VTEC infection in the Republic of Ireland is particularly associated with rural areas, which are associated with a ubiquity of pathogen sources (cattle) and pathways (unregulated groundwater supplies).

A comparative study of the spatial distribution of HIV prevalence in the metropolis of Kermanshah, Iran, in 1996-2014 using geographical information systems

OBJECTIVES

Geographical information systems (GISs) have made spatiotemporal understanding of geographical patterns possible and have contributed to the identification and analysis of factors relating to health care behaviours and outcomes. The present study is the first to examine the spatial distribution of HIV prevalence in the metropolis of Kermanshah, Iran, using GISs.

METHODS

The research methods were descriptive, analytical and comparative. Additionally, data recorded for HIV-infected patients in 1996-2014 were used and then the loci of HIV infection in the metropolis of Kermanshah were identified and analysed spatially using ArcGIS (Esri, New York, NY, USA).

RESULTS

HIV prevalence in the metropolis of Kermanshah increased from 1996 to 2014. Analysis of the spatial distribution of the prevalence of HIV using ArcGIS indicated the presence of clusters of HIV infection. The findings demonstrate that there were many clusters of high HIV prevalence throughout the city of Kermanshah and that these clusters increased in size during the study period. Furthermore, the statistics are indicative of a growing number of HIV-infected women as well as a significant reduction in the mean age of the HIV-infected female population.

CONCLUSIONS

The spatial differences in HIV prevalence across the city of Kermanshah, as well as the identification of the resulting spatial clusters in different parts of the city, suggest that measures should be put in place to prevent the growth of these clusters and to reduce the number of women being infected with HIV.

Climate and local abundance in freshwater fishes

Identifying factors regulating variation in numbers of individuals among populations across a species' distribution is a fundamental goal in ecology. A common prediction, often referred to as the abundant-centre hypothesis, suggests that abundance is highest near the centre of a species' range. However, because of the primary focus on the geographical position of a population, this framework provides little insight into the environmental factors regulating local abundance. While range-wide variation in population abundance associated with environmental conditions has been investigated in terrestrial species, the relationship between climate and local abundance in freshwater taxa across species' distributions is not well understood. We used GIS-based temperature and precipitation data to determine the relationships between climatic conditions and range-wide variation in local abundance for 19 species of North American freshwater fishes. Climate predicted a portion of the variation in local abundance among populations for 18 species. In addition, the relationship between climatic conditions and local abundance varied among species, which is expected as lineages partition the environment across geographical space. The influence of local habitat quality on species persistence is well documented; however, our results also indicate the importance of climate in regulating population sizes across a species geographical range, even in aquatic taxa.

Pediatric dental clinic location and utilization in a high-resource setting

OBJECTIVES

Examine dental utilization by Medicaid-insured children living in a high-resource area. Characterize distance and travel-related variables to accessing care.

METHODS

Cross-sectional data were collected on dental clinics in Pittsburgh, Pennsylvania, caring for Medicaid-insured children ≥1 year. Shortest distances, drive times, and bus travel between dental clinics and high-poverty census tracts were determined through geographical information systems analysis. Primary care clinic (PCC) survey data were analyzed for children's dental use. Demographic characteristics and travel-related variables were compared between children who had and had not been to a dentist.

RESULTS

Ten dental clinics accepted Medicaid-insured children ≥1 year. Mean distance between high-poverty census tracts and their nearest clinic was 1.2 miles [standard deviation (SD) 0.2 miles], with mean bus travel time 15.6 minutes (SD 12.3 minutes). Overall, 46 percent of PCC children reported a dental visit, and this was not significantly different between those who lived in a high-poverty census tract versus those who did not (41 percent and 35 percent, respectively, P = 0.58). Children traveled a mean distance of 4.75 miles (SD 2.37 miles) to their dental clinic. Mean distance to their nearest dental clinic was 2.81 miles (SD 2.12 miles).

CONCLUSION

Dental clinics in a high-resource area are in close proximity to where young Medicaid-insured children live; and distances between children's homes and dental clinics are not significantly different between children who had and had not reported a dental visit, suggesting that barriers persist despite close proximity. Regardless, closer proximity may contribute to the higher utilization of services observed compared with national rates.

The public health exposome: a population-based, exposure science approach to health disparities research

The lack of progress in reducing health disparities suggests that new approaches are needed if we are to achieve meaningful, equitable, and lasting reductions. Current scientific paradigms do not adequately capture the complexity of the relationships between environment, personal health and population level disparities. The public health exposome is presented as a universal exposure tracking framework for integrating complex relationships between exogenous and endogenous exposures across the lifespan from conception to death. It uses a social-ecological framework that builds on the exposome paradigm for conceptualizing how exogenous exposures "get under the skin". The public health exposome approach has led our team to develop a taxonomy and bioinformatics infrastructure to integrate health outcomes data with thousands of sources of exogenous exposure, organized in four broad domains: natural, built, social, and policy environments. With the input of a transdisciplinary team, we have borrowed and applied the methods, tools and terms from various disciplines to measure the effects of environmental exposures on personal and population health outcomes and disparities, many of which may not manifest until many years later. As is customary with a paradigm shift, this approach has far reaching implications for research methods and design, analytics, community engagement strategies, and research training.

The influence of the built environment on outcomes from a "walking school bus study": a cross-sectional analysis using geographical information systems

Active commuting to school increases children's daily physical activity. The built environment is associated with children's physical activity levels in cross-sectional studies. This study examined the role of the built environment on the outcomes of a "walking school bus" study. Geographical information systems was used to map out and compare the built environments around schools participating in a pilot walking school bus randomised controlled trial, as well as along school routes. Multi-level modelling was used to determine the built environment attributes associated with the outcomes of active commuting to school and accelerometer-determined moderate-to-vigorous physical activity (MPVA). There were no differences in the surrounding built environments of control (n = 4) and intervention (n = 4) schools participating in the walking school bus study. Among school walking routes, park space was inversely associated with active commuting to school (β = -0.008, SE = 0.004, P = 0.03), while mixed-land use was positively associated with daily MPVA (β = 60.0, SE = 24.3, P = 0.02). There was effect modification such that high traffic volume and high street connectivity were associated with greater moderate-to-vigorous physical activity. The results of this study suggest that the built environment may play a role in active school commuting outcomes and daily physical activity.

Habitat evaluation for outbreak of Yangtze voles (Microtus fortis) and management implications

Rodent pests severely damage agricultural crops. Outbreak risk models of rodent pests often do not include sufficient information regarding geographic variation. Habitat plays an important role in rodent-pest outbreak risk, and more information about the relationship between habitat and crop protection is urgently needed. The goal of the present study was to provide an outbreak risk map for the Dongting Lake region and to understand the relationship between rodent-pest outbreak variation and habitat distribution. The main rodent pests in the Dongting Lake region are Yangtze voles (Microtus fortis). These pests cause massive damage in outbreak years, most notably in 2007. Habitat evaluation and ecological details were obtained by analyzing the correlation between habitat suitability and outbreak risk, as indicated by population density and historical events. For the source-sink population, 96.18% of Yangtze vole disaster regions were covered by a 10-km buffer zone of suitable habitat in 2007. Historical outbreak frequency and peak population density were significantly correlated with the proportion of land covered by suitable habitat (r = 0.68, P = 0.04 and r = 0.76, P = 0.03, respectively). The Yangtze vole population tends to migrate approximately 10 km in outbreak years. Here, we propose a practical method for habitat evaluation that can be used to create integrated pest management plans for rodent pests when combined with basic information on the biology, ecology and behavior of the target species.

Heterogeneity in hotspots: spatio-temporal patterns in neglected parasitic diseases

Cryptosporidiosis and giardiasis have been recognized by the WHO as 'Neglected Diseases'. Minimal attention has been paid to the spatial and temporal distribution of disease incidence patterns. Using disease notification data, we detected spatio-temporal clusters of cryptosporidiosis and giardiasis across three time periods: (i) 1997-2000, (ii) 2001-2004, (iii) 2005-2008. There was substantial variation in the geographical location and timing of recurrent cryptosporidiosis and giardiasis clusters. Statistically significant (P < 0·05) giardiasis clusters tended to occur in predominantly urban areas with little apparent seasonal influence, while statistically significant cryptosporidiosis clusters were detected in spring, in areas with high livestock land use. The location and timing of cryptosporidiosis clusters suggest an influence of livestock production practices, while urban exposures and host behaviour are likely to influence giardiasis clusters. This approach provides a resource-efficient method for public health authorities to prioritize future research needs and areas for intervention.

Battling Malaria in Rural Zambia with Modern Technology: A Qualitative Study on the Value of Cell Phones, Geographical Information Systems, Asymptomatic Carriers and Rapid Diagnostic Tests to Identify, Treat and Control Malaria

During the last decade much progress has been made in reducing malaria transmission in Macha, Southern Province, Zambia. Introduction of artemisinin combination therapies as well as mass screenings of asymptomatic carriers is believed to have contributed the most. When an endemic malaria situation is moving towards a non-endemic situation the resident population loses acquired immunity and therefore active case detection and efficient surveillance is crucial to prevent epidemic outbreaks. Our purpose was to evaluate the impact of cell phone surveillance and geographical information systems on malaria control in Macha. Furthermore, it evaluates what screening and treatment of asymptomatic carriers and implementation of rapid diagnostic tests in rural health care has led to. Ten in-depth semi-structured interviews, field observations and data collection were performed at the Macha Research Trust and at surrounding rural health centers. This qualitative method was inspired by rapid assessment procedure. The cell phone surveillance has been easily integrated in health care, and its integration with Geographical Information Systems has provided the ability to follow malaria transmission on a weekly basis. In addition, active case detection of asymptomatic carriers has been fruitful, which is reflected in it soon being applied nationwide. Furthermore, rapid diagnostic tests have provided rural health centers with reliable malaria diagnostics, thereby decreasing excessive malaria treatments and selection for drug resistance. This report reflects the importance of asymptomatic carriers in targeting malaria elimination, as well as development of effective surveillance systems when transmission decreases. Such an approach would be cost-efficient in the long run through positive effects in reduced child mortality and relief in health care.

Ecological screening indicators of stress and risk for the Llobregat river water

The objective of this article is to develop and apply several simple and rough indicators for river aquatic ecosystems assessment in order to screen potential chemical stressors. Several indicators, based on toxicity (PNEC) and on legislation levels (EQS) have been developed. All these indicators are ratios that were calculated by using public and private data of concentrations of a large list of compounds during a period of five years, including metals and organic compounds in the lower part of the Llobregat river basin at the intake of the drinking water treatment plant. Additionally, new campaigns were executed for increasing the information available on the presence of compounds not routinely analyzed, such as some other pesticides and pharmaceuticals. In the case of inorganic pollutants, the indicators obtained in this river section showed significant risk especially for zinc, but also for copper, nickel and barium. For organic pollutants, the pesticides terbuthylazine, diazinon, 2-methyl-4-chlorophenoxyacetic (MCPA), and in a few cases, chlorpyrifos and lindane, also showed indexes above the threshold. Among the pharmaceuticals, the antibiotics clarithromycin and ciprofloxacin were the only ones with risk indicators adverse to ecosystems. The specific values of the indexes obtained rely on the quantity and quality of the data available, so their interpretation should take into account that some values can be high due to the use of too conservative toxicological information.

Blood donation clusters in Québec, Canada (2003-2008): spatial variations according to sex and age

BACKGROUND AND OBJECTIVES

The detection of spatial clusters of blood donation rate is an important issue, especially for targeting spatial units with significantly low rates, where it could be possible to increase the numbers of donors. The objective of this study is to detect spatial clusters of high or low blood donation rate in Québec according to sex and age of the donors.

MATERIALS AND METHODS

Blood donation data were obtained from Héma-Québec over a period of 5 years. We aggregated these data for each of 101 municipalités regionales de comté (i.e. counties) for men, women and four age groups. To detect spatial high/low donation rate areas, we used the Kulldorff's scan statistics. Kappa coefficient was used to assess discordance between clusters obtained for the different groups (18-29, 30-39, 40-49, 50-59, 60-69 years old). T-test analyses were conducted to identify significant associations between spatial clusters and socio-economic variables.

RESULTS

The results indicate the presence of several geographical areas with high or low blood donation rates for each group. The size, the location and the socio-demographic profiles of low/high clusters vary according to sex and age categories.

CONCLUSION

The Kulldorff's scan statistics are an efficient tool to assess the blood donation performance across a country or even a specific region over a period of several years. In terms of strategic planning and monitoring, it can be used as a fully operational tool to target areas with significantly low rates (for all donors or specific demographic groups) in future blood donation campaigns.

Exploratory Spatial Mapping of the Occurrence of Antimicrobial Resistance in E. coli in the Community

The use of antimicrobials over the past six decades has been associated with the emergence and dissemination of antimicrobial-resistant bacteria. To explore local geographical patterns in the occurrence of acquired antimicrobial resistance (AMR), AMR of E. coli causing urinary tract infections (UTI) in the community in the West of Ireland was mapped. All adult patients consulting with a suspected UTI in 22 general practices in the West of Ireland over a nine-month study period were requested to supply a urine sample. Those with a laboratory confirmed E. coli infection were included (n = 752) in the study. Antimicrobial susceptibility testing was performed by standardized disc diffusion. Patient addresses were geocoded. The diameters of the zone of inhibition of growth for trimethoprim (5 μg) and ciprofloxacin (5 μg) for the relevant isolate was mapped against the patient address using ArcGIS software. A series of maps illustrating spatial distribution of AMR in the West of Ireland were generated. The spatial data demonstrated a higher proportion of isolates with AMR from urban areas. Some rural areas also showed high levels of resistant E. coli. Our study is the first to demonstrate the feasibility of using a geographical information system (GIS) platform for routine visual geographical analysis of AMR data in Ireland. Routine presentation of AMR data in this format may be valuable in understanding AMR trends at a local level.

Geographic patterns of hepatocellular carcinoma mortality with exposure to iron in groundwater in Taiwanese population: an ecological study

BACKGROUND

Many studies have examined the risk factors for HCC (including hepatitis B virus, hepatitis C virus, aflatoxin, retinol, cigarette smoking, and alcohol consumption). However, data from previous studies on the association between iron exposure, land subsidence, and HCC mortality/incidence were limited, especially in Taiwanese population. We aimed to explore the geographical distribution of HCC mortality rates by township-specific data and to evaluate the association between HCC mortality, land subsidence, and iron levels in groundwater in Taiwan.

METHODS

We conducted an ecological study and calculated the HCC age-standardized mortality/incidence rates according to death certificates issued in Taiwan from 1992 to 2001 and incidence data from 1995-1998. The land subsidence dataset before 2005 and iron concentrations in groundwater in 1989 are also involved in this study. Both geographical information systems and Pearson correlation coefficients were used to analyze the relationship between HCC mortality rates, land subsidence, and iron concentrations in groundwater.

RESULTS

Township-specific HCC mortality rates are higher in southwestern coastal townships where serious land subsidence and higher township-specific concentrations of iron in groundwater are present. The Pearson correlation coefficients of iron concentrations in groundwater and ASRs of HCC were 0.286 (P = 0.004) in males and 0.192 (P = 0.058) in females for mortality data; the coefficients were 0.375 (P < 0.001) in males and 0.210 (P = 0.038) in females for incidence data.

CONCLUSIONS

This study showed that HCC mortality is clustered in southwestern Taiwan and the association with the iron levels in groundwater in Taiwanese population warrant further investigation.

Spatial and temporal patterns of dengue in Guangdong province of China

The aim of the study was to describe the spatial and temporal patterns of dengue in Guangdong for 1978 to 2010. Time series analysis was performed using data on annual dengue incidence in Guangdong province for 1978-2010. Annual average dengue incidences for each city were mapped for 4 periods by using the geographical information system (GIS). Hot spot analysis was used to identify spatial patterns of dengue cases for 2005-2010 by using the CrimeStat III software. The incidence of dengue in Guangdong province had fallen steadily from 1978 to 2010. The time series was a random sequence without regularity and with no fixed cycle. The geographic range of dengue fever had expanded from 1978 to 2010. Cases were mostly concentrated in Zhanjiang and the developed regions of Pearl River Delta and Shantou.

A multi-stage approach to maximizing geocoding success in a large population-based cohort study through automated and interactive processes

To enable spatial analyses within a large, prospective cohort study of nearly 86,000 adults enrolled in a 12-state area in the southeastern United States of America from 2002-2009, a multi-stage geocoding protocol was developed to efficiently maximize the proportion of participants assigned an address level geographic coordinate. Addresses were parsed, cleaned and standardized before applying a combination of automated and interactive geocoding tools. Our full protocol increased the non-Post Office (PO) Box match rate from 74.5% to 97.6%. Overall, we geocoded 99.96% of participant addresses, with only 5.2% at the ZIP code centroid level (2.8% PO Box and 2.3% non-PO Box addresses). One key to reducing the need for interactive geocoding was the use of multiple base maps. Still, addresses in areas with population density <44 persons/km2 were much more likely to require resource-intensive interactive geocoding than those in areas with >920 persons/km2 (odds ratio (OR) = 5.24; 95% confidence interval (CI) = 4.23, 6.49), as were addresses collected from participants during in-person interviews compared with mailed questionnaires (OR = 1.83; 95% CI = 1.59, 2.11). This study demonstrates that population density and address ascertainment method can influence automated geocoding results and that high success in address level geocoding is achievable for large-scale studies covering wide geographical areas.

Land elevation and cancer mortality in u.s. Cities and counties using median elevations derived from geographic information systems

There are a number of variables that are correlated with land elevation. Land elevation, and in particular, its surrogate variables such as natural background radiation, can be studied in relation to cancer rates. The present ecological study focuses on three such variables correlated with land elevation: natural background radiation (NBR), oxygen concentration (OC), and barometric pressure (BP). In addition, the study uses a novel approach for determining median land elevation values from which the surrogated variables are estimated. Inverse correlations were observed for NBR while direct correlations were found for OC and BP suggesting the presence of a protective effect with all three variables. Further study is indicated to either verify or refute these findings.

Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control

This paper reviews recent studies on the spatial epidemiology of human schistosomiasis in Africa. The integrated use of geographical information systems, remote sensing and geostatistics has provided new insights into the ecology and epidemiology of schistosomiasis at a variety of spatial scales. Because large-scale patterns of transmission are influenced by climatic conditions, an increasing number of studies have used remotely sensed environmental data to predict spatial distributions, most recently using Bayesian methods of inference. Such data-driven approaches allow for a more rational implementation of intervention strategies across the continent. It is suggested that improved incorporation of transmission dynamics into spatial models and assessment of uncertainties inherent in data and modelling approaches represent important future research directions.

Dead bird clusters as an early warning system for West Nile virus activity

An early warning system for West Nile virus (WNV) outbreaks could provide a basis for targeted public education and surveillance activities as well as more timely larval and adult mosquito control. We adapted the spatial scan statistic for prospective detection of infectious disease outbreaks, applied the results to data on dead birds reported from New York City in 2000, and reviewed its utility in providing an early warning of WNV activity in 2001. Prospective geographic cluster analysis of dead bird reports may provide early warning of increasing viral activity in birds and mosquitoes, allowing jurisdictions to triage limited mosquito-collection and laboratory resources and more effectively prevent human disease caused by the virus. This adaptation of the scan statistic could also be useful in other infectious disease surveillance systems, including those for bioterrorism.

Modeling population access to New Zealand public hospitals

This paper demonstrates a method for estimating the geographical accessibility of public hospitals. Cost path analysis was used to determine the minimum travel time and distance to the closest hospital via a road network. This analysis was applied to 38,000 census enumeration district centroids in New Zealand allowing geographical access to be linked to local populations. Average time and distance statistics have been calculated for local populations by modeling the total travel of a population if everybody visited a hospital once. These types of statistics can be generated for different population groups and enable comparisons to be made between regions. This study has shown that the northern and southern parts of New Zealand have high average travel times to hospital services.

Geographical Information System (GIS) as a tool in surveillance and monitoring of animal diseases

In the veterinary epidemiology, the advantage of mapping the locations of farms and other facilities with animals is obvious. In an outbreak of a disease it could make the management of the situation easier, and it could also provide a tool to evaluate different strategies to prevent the spread of infectious diseases. This paper aims to describe and give an overview of the possibilities and potential uses of a Geographical Information System (GIS) in the field of surveillance and monitoring of animal diseases. The following areas in which GIS and special GIS-functions could be incorporated are presented: recording and reporting information, epidemic emergency, cluster analysis, modelling disease spread, and planning control strategies. Different sources of data; geographical data, farm locations and disease information, used in the development of the GIS at the National Veterinary Institute in Norway are thoroughly described in the paper. Further, it presents a few examples where the GIS has been applied to studies of epidemiology and surveillance of animal diseases in Norway, which shows the significant value of GIS in these areas. At the same time, the incorporation of GIS in this field shows the scarcity of the data available, which should encourage improvement in the data recording and the quality of the registries.